(ecology and climate change from the 4th dimension)

How to argue with a scientist: A guide

I notice it all the time– on Facebook, in the comments of a science blog, over family gatherings, or listening to a radio talk show. Someone, maybe you, is patiently trying to explain how vaccines cause autism, perhaps, or why so-called “anthropogenic” global warming is really just due to sunspots or some other natural cycle. Perhaps you are doing pretty well at first, making use of passionate, heart-felt rhetoric and well-timed anecdotes. People are nodding their heads in agreement, and perhaps you’re even changing someone’s mind.

And then a scientist joins the discussion.

The conversation tends to devolve from here, turning into a debate and (often) ultimately a debacle. Scientists are notoriously difficult to argue with– for one, they’re so sure they’re right! This is true of most people, though– and it’s probably true of you. What makes it especially frustrating to argue with a scientist is the jargon they use; if you don’t speak their language, you’re probably not going to change their mind.

I have created this handy guide to arguing with a scientist precisely for people like you! I’ve collected the most commonly used phrases and translated them into everyday English, so that the next time you argue with a scientist, you’ll not only better understand their arguments, but you might learn how to make yours better, too.*

Sample size: Sample size, often referred to by scientists as “n” (as in, “number”) is how many observations went into a particular study. In other words, if you interviewed twenty of your co-workers on whether donuts should be provided at meetings, then your sample size would be 20 (or, “n = 20″). For scientists, sample size is huge (er, pun intended)– the bigger the n, the better. If you only asked two of your colleagues in your survey, you might randomly pick the two that hate donuts, and that would result in donut-less meetings! Scientists talk about sample size in arguments all the time, to convince you that they have more “data” (evidence) to support their claim than you do. For example, if you say that there is one study that proves that global warming is natural, but the scientist cites 10,038 studies, their n = 10,038 and yours = 1. You’re definitely going to need a bigger sample size to win this argument! Sample size could refer to the number of subjects in a test (like the number of interviewees in the donut study) or even the number of studies themselves (maybe you conducted two sets of interviews at two businesses). So why is more, well, more? Bigger sample sizes give you a better sense of the natural range your data might have (aka opinions on donuts), and you’re less likely to draw the false conclusion that people hate donuts because you didn’t ask enough people.

Made with the Einstein Chalkboard Generator (click for link).

Anecdotal evidence: This is related to sample size. An anecdote is a story– like that one about the time that Aunt Millie’s poodle ate four loaves of fruitcake and, well, you get the idea. Scientists are not fond of anecdotes, as a general rule. They’re not very, well, scientific (more on this later). Basically, your anecdote about your chain-smoking uncle who lived to be 98 is like having a sample size of 1, and it doesn’t hold up to the hundreds of studies that show a link between cigarettes and cancer. In fact, your anecdote isn’t even as good as a sample size of 1 in this case, because the anecdote is a story, and not a scientific study (remember, each study tends to have a lot of subjects, so really your sample size is closer to 0.001). Anecdotes are messy– they aren’t set up like proper experiments, with regulations and control groups. Your anecdote may be a really powerful story, and it may help to illustrate a point, but it won’t win an argument with a scientist. When a scientist says, “the plural of ‘anecdote’ isn’t ‘data'” , this is what they’re referring to: a story isn’t sufficient evidence to draw a strong conclusion. Scientific studies may have problems, but they’re still better evidence than a story (I may have just made up that story about Aunt Millie’s poodle, and you’d have no way of knowing!). If you want to convince a scientist, you have to show them real evidence.

“That’s not scientific!” A common critique from scientists is that something isn’t “scientific.” By this, they don’t mean that you didn’t come to your conclusion using test tubes and wearing a lab coat. Really, for something to be scientific, it needs to be done according to the Scientific Method– that is, you formulate a hypothesis (an idea about how the world works) and you test that hypothesis by experimenting or collecting data, and you repeat this process as much as possible until you better understand whatever it is you’re trying to learn more about. Obviously, this is tricky for a non-scientist to do, but you can limit yourself to arguing about things that are scientific! For something to be scientific, you have to be able to take a measurement of something– that is, it has to be “quantifiable” (which has the same root as the word “quantity”). Things like how much you love your cat or whether the Flying Spaghetti Monster made the universe are not quantifiable, because they can’t be measured. Therefore, they are not scientific. That doesn’t mean you can’t have real feelings or meaningful discussions about them, it just means that those discussions are not in the realm of Science. You can make an emotional, moral, or philosophical argument when debating with a scientist, but just be really clear that you’re using a different kind of criteria. For example, we can talk about whether it’s possible to clone Neanderthals to see if they had speech, and we can talk about whether cloning Neanderthals is morally and ethically right.

Peer review: Scientists just love to use peer review in arguments! You can show them all the well-written blog posts, internet surveys, magazine articles, interviews, and anecdotes you want, but scientists put much more stock in peer reviewed studies. By “peers,” they mean fellow scientists. This may at first sound like something of a Good Old Boys’ Club, where scientists sit around and pat one another on the back for yet another brilliant deduction. This is actually not the case! Scientists conduct experiments and collect data, write up that data into an article, and try to get that article published in a scientific journal (basically, a magazine for scientists that mostly only publishes the results of experiments). Many, many of these papers get rejected every day! Scientists can be very hard on one another, and often disagree on major ideas and finer details of methods, interpretation of data, or theories. Sometimes, experiments are just plain badly designed, or the conclusions are too strong and not supported by enough evidence. When a paper comes out in a journal after peer review, it means it’s been refereed by at least a few scientists in the field. Peer review can have its problems (you sometimes get an inappropriate editor, or perhaps easy or harsh reviewers due to luck of the draw), but that’s where sample size comes in. If you have a lot of peer-reviewed papers (a large sample size!), chances are that this effect evens out and you can come to some real conclusions.

To win an argument with a scientist, you need to cite peer-reviewed research. A website with a poll linking vaccines to autism is useless; anyone could have made up the data, for example, and your results are skewed to only those people visiting that website already (so, a specific subset of the population). With peer review, you at least know that the publication has undergone scrutiny by other experts. What’s more, once the paper comes out in a journal, scientists see it and continue the discussion by doing their own studies. If a scientist disagrees with a paper, they may even submit a letter to the journal explaining why. But with blog posts, or magazine articles– even well-written and well-researched ones– the rules are different. One problem is that non-scientists (maybe you!) often don’t have access to peer-reviewed articles (many are subscription-only), and so you can be at a disadvantage. But if you can cite peer-reviewed studies, or ask the scientist to, then your arguments will be much stronger. When you read a blog post or an article, check to see if they’re citing good sources, too.

Bias: When arguing with a scientist, you want to avoid using lines of evidence that come from what could be called “biased” sources–that is, sources that may have a vested interest in holding a different conclusion than that drawn from the evidence. For example, if you were trying to argue (still) that cigarettes don’t cause cancer, you wouldn’t want to back up your argument with a website run by a tobacco company. The tobacco company has an agenda (to sell cigarettes) and are therefore unlikely to share information that detracts from this agenda. “But what about scientists?” you might argue. “Isn’t the pursuit of science a sort of agenda itself?” Sure, and scientists do have their own biases (which could be the subject of an entire blog). However, at the end of the day, whether (most) scientists make money doesn’t depend on their research results. Publicly funded scientists (those who fund their work from research grants that come from taxpayer dollars) get paid to do research, not to come up with particular conclusions. Ultimately, peer-reviewed climate research is just more trustworthy than research paid for by an oil company, for example. If you want to win an argument with a scientist, be very careful about the kinds of evidence you’re citing, where it came from, and who paid for it.

Consensus: Scientists often use “consensus” as the ultimate argument-winner, and for good reason. Scientific consensus is the collected opinions of all scientists, and not just the one you’re arguing with. There can be one or two scientists who disagree (just like there are a handful of people who don’t believe the Holocaust happened), but if the vast majority of scientists have reached consensus, it means that there is so much evidence in support of an idea that it’s basically a guaranteed thing, based on state-of-the-art knowledge. Remember that scientists often disagree, have debates, argue, and may spend entire careers fighting one another. The reason scientists generally reach consensus with other scientists (and not, say, your UFO abudction group) is because other scientists also use the Scientific Method, publish in peer-reviewed journals, and are informed by some of the basic principles I’ve explained above. Consensus is a powerful thing, and in some ways it’s amazing that scientists ever reach it at all! In other words, if a scientist says that the consensus is that you are wrong, there is probably nothing you can do. Unfortunately, saying, for example, “well, the consensus among my abduction support group is that UFO’s did build the Pyramids!” isn’t going to sway them, because you probably a) don’t have peer-reviewed studies, and b) rely on anecdotes (see above).

If you’ve struggled with arguing with scientists, it’s understandable! After reading this guide, you may realize that scientists can have very different worldview than many people, due to their training and the tools they use– In fact, there are entire branches of study that are involved with understanding scientists’ outlook and how it’s changed through time. Having a different worldview can make scientists especially tricky to argue with, but it can be done (which is proven by they very fact that they argue among themselves all the time!). Scientists may seem like robots, but they in fact make mistakes, have emotions, and are biased, just like everyone else (including you!). Just remember that 1) behind the jargon, scientists are human beings, and most of them can really be very nice people, and 2) you don’t have to be a scientist to successfully argue with one!

*Insert many caveats about generalizations and oversimplifications here. This is meant to be an introductory guide, not a thorough treatise. Historians and philosophers of science will likely cringe, but the goal here is the edification of the layperson.

On this discussion I do not have much input for I have never talked to a scientist. Therefore any input that I add would be considered invalid. I am confused on this subject and what everyone is talking about. But I do know that scientist think they are their own breed.

Your view of science is far too idealistic. In theory science should work somewhat as you described, but the reality differs greatly. There’s far too much politics in science (and no I don’t mean political parties), and the pursuit of funding greatly distorts what gets studied. Science eventually gets things right, but the process is much slower than it needs to be. Although some of the comments here are insightful, most of them serve to illustrate the types of problems that exist in science.

Reblogged this on disrupt learning! and commented:
I was all set to write my own blog post, “How to Argue with a Scientist” today (after some unfortunate interactions with non-scientists last week), but Jacquelyn already beat me to it!

The one addition I would make to her article is that many of us in the behavioral and learning sciences conduct single-subject research. We, of course, use the scientific method, and the extreme rigor of our experimental methodology obviates the need for inferential statistics, thereby allowing us to use a much smaller sample size than Jacquelyn describes here. Have fun reading this! It rocks!

Very fun post! I had an argument last week with a non-scientist and was going to write my own blog post with your same title today! Now I’m going to repost yours! Would love for you to visit my site: http://www.karenmahon.com

The one caveat that I would add is that there is a large population of us behavioral scientists who do single-subject research. Still scientific method and very rigorous experimental design; because of the methodological rigor that obviates the need for inferential statistics, we require a much smaller sample size.

I also disagree with the argument on consensus. Every major theory or idea that collapses is preceded by a period of consensus during which most people believed the ultimately failed theory was true. Consensus views of various scope are overturned almost daily across the range of scientific inquiry.

The true test of a scientific idea or theory is whether or not it can be proven by repeatable experiments.

Nothing in science is ever proven. No experiment ever “proves” a scientific theory.

Compelling scientific theories are considered true because no known evidence contradicts them — that is, despite the best efforts of the scientific community, the theory has not been disproven. Yet. Scientists continue to try to devise an experiment that contradicts general relativity or the standard model of quantum physics.

Actual scientists mostly seek evidence that will contradict and thus disprove a favored idea.
Pseudo-scientists mostly cherry-pick evidence that seems to support a favored idea.

Brett’s argument is offensive and impolite, but well-written – he’s probably sober and educated, and from that I can assume that he’s aware of the effect it has on me as a scientist and environmentalist, and intends that effect. Just for the sake of practice – and in case he is capable of critical thinking and willing to engage in a debate with someone who doesn’t dismiss him outright – I would submit this argument.

I accept that that scientists can be subject to bias, and that their work can be selectively published by their employers for the benefit of their employers; and that this bias and selectivity can be influenced by many things, including recognition and money. What I would like from someone making Brett’s argument (that scientists publishing papers supporting anthropogenic climate change are altering or cherry-picking their results in order to secure more funding) is some (retrospective) research regarding funding and results published. I am not a social scientist, so I am certainly not qualified to lay out the experiment, but it would be something along these lines:

(Note that this does NOT deal with results filtered by employers with vested interests, this would overcomplicate the experiment and should be addressed separately).

To show that a particular group of scientists are altering their published results in order to secure funding , you would have to show three things: One, that a certain conclusion (‘people cause global warming’) leads to an increase in funding, whereas the opposite conclusion does NOT; Two, that an increase in funding leads to an increase in the number of papers published that support that conclusion; and Three, that a second group of scientists who’s pay or funding does NOT depend on the particular conclusions they publish would NOT come to the same conclusion (‘people cause global warming’) with the same frequency as the group that is effectively being rewarded for one conclusion over another.

The goal is to show that funding – and nothing else – is influencing the results that these scientists publish. Examples of other things which could influence the results published by scientists (the things we must ‘control for’) include: a personal non-financial preference for certain results (“I wish this was true because it makes me feel good”); a desire to publish a popular result; or the actual truth. All of these things are controlled for in the second (‘control’) group of scientists.

I doubt that this experiment has been done – but forgive me if it has; I certainly haven’t thoroughly searched the literature to find out, and it is of course possible that it has been done but is suppressed. Brett will probably have to do the experiment himself, if he feels strongly enough about the subject; that is, after all, the way of a scientist – if a question hasn’t been answered to your satisfaction, apply yourself to answering it.

To complete the experiment, it would be necessary to follow the scientific method – not because it has to be made acceptable to scientists, but because there is no other way to conduct an experiment in a way that respects logic, personal bias (because everyone has one, and it ought to be respected by an honest experimenter), and the complications of real life. If you design an experiment that meets rigorous standards for those things, you will have followed the scientific method – even if unintentionally. Brett can undoubtedly do just that, given enough time and access to the right data.

This has been a useful exercise for me, to practice the points mentioned in this blog. As a scientist, I needed reminding of what some people might not understand the way I do; and the process of dissecting the scientific method for someone unfamiliar with it has increased my understanding of it. Thank you.

Excellent! Although I do take exception to likening doubt of the consensus with holocaust denial. While I understand where that sentiment comes from, some great science has been done overturning consensus.

Fair enough! Plate tectonics and the K-T Event would be examples of positive consensus turnover. I struggled to find an non-science analog with just a handful of detractors- The Holocaust was all I could think of.

Quasi-crystals is another one! Was worth a noble prize. Actually the consensus is quiet often overturned…so it’s always worth ‘thinking outside the box’. And as a scientist, I’m unfortunately losing faith in the power of peer review. Bottom line is the major journals want highly discussed “ground-breaking” research whether it’s reproducible or not. Unfortunately, it too often turn outs not to be reproducible (or at least not reproducible in the manner implied/described by the primary paper). While these papers undergo extensive peer-review, the final line relies on the honestly of the researcher and naturally there are individuals who exploit this. Anyway, I think the main reason not to argue not to argue with a scientist is because we’re always right ; )

I totally agree. I will make myself available to any reasonable person who wants to have a conversation about darn near anything even if they disagree with me. (but that’s not Brett)
I teach at a community college/4 year school so I spend a lot of time doing ‘outreach’ not just in class but in the community as well and I do appreciate your sense of duty as a publicly funded scientist.

It is an understatement that there is a tremendous gap between the public and the scientist – the gap is not in knowing about things like dark energy, the greenhouse effect, or germ theory. The gap is in ‘how to think about these things’. This gap is tragic. When it comes to immunization it can be lethal.

Many non-scientists love hearing about research. In fact, cable TV has whole channels devoted to sharing science with the public. There are numerous magazines which popularize science. Also, most major cities have a planetarium, aquarium, zoo, and various science museums. According John Falk’s research, informal science education makes the American public among the most science literate in the world.

The public knows about so many natural processes and phenomena and yet somehow largely lacks the mental techniques to work with that knowledge. we need to remedy this! We all can do better – there are even some scientists who don’t seem to apply these techniques outside of their field of expertise, such as Linus Pauling and Freeman Dyson).

Actually, the plural of “anecdote” IS “data”. The adage comes from a misquote. Your explanation of sample size stands, but it’s the sample size that make an anecdote weak evidence, not whether or not it qualifies as a data point.

Actually, it’s a bit more complicated than that, as you can see here: http://bearcastle.com/blog/?p=408. The jury may be out, but the earliest attribution includes “not.”

I also disagree that sample size alone that makes anecdotes weak evidence. Anecdotal evidence includes (but is not limited to) the use of anecdotes, which may themselves be cherry-picked, second-hand, or even falsified. Anecdotal evidence includes evidence that is itself not scientific, and therefore generally considered inappropriate.

Not at all. As a paleoecologist, I would hardly make that argument! :) I meant that anecdotes, as a general layperson would use them in an argument, are not scientific. Retrospective studies have their own problems, which is another topic entirely, but I also wouldn’t call “my uncle so-and-so worked with asbestos all his life!” on par with a retrospective study. I don’t have a problem with qualitative data, either– many of my colleagues in Geography use qualitative methods. Each type of data has its own issues, and they’re not always comparable.

I was pretty clear that this was meant as a general introduction (and a tongue-in-cheek one at that). I realize that I’m making many generalizations and simplifications. I’m also coming from the perspective of an ecologist and climate scientist, and not a sociologist or medical scientist, for example.

The problem with anecdotes as data is that they’re interesting (or they wouldn’t have hung around to be retold): they tend to be the stories that prove a point or have something worth remembering – as well as being cherry-picked to support an argument, they will very frequently be derived from the most outlying of outliers, like your 98-year-old chainsmoking uncle.

The reason (well, one reason, anyway) that a large sample size of anecdoes cannot be considered scientific data is this filtering: there’s no way of knowing from one story or ten whether behind that there are a dozen or a million cases which weren’t sufficiently interesting to be retold. Obviously this can be a problem with retrospective studies, but isn’t that kind of where the skill is in that kind of work?

Nice article, btw: there’s been many a time when I’ve had to try and explain to non-scientific friends why what they read on the internet somewhere (or in the Daily Mail) doesn’t consititute an argument, let alone proof.

In case anyone misreads ‘not scientific’ to mean ‘we scientists ignore it because we don’t like it’, the point is that evidence needs to be assembled in a controlled way before we can tell what conclusions we can or can’t draw from it. A study comparing two groups of patients whose cases were very similar apart from one identical, controlled difference (e.g. receiving drug A or drug B) can provide evidence; a collection of anecdotes can’t provide the same level of evidence because we don’t know what other factors differed between the different cases.

A retrospective study likewise involves assembling enough information about the cases (patients, samples, whatever) that we can tell what conclusions we can or can’t draw from the outcomes, it’s just a bit harder to do because you aren’t planning in advance what data to collect.

It’s not just the sample size, though. It’s also the fact that anecdotes are not controlled. IPU knows how many confounding factors there are obscuring the effect of the one cause the anecdote teller is trying to show. (My favourite example to use is the claim of a herbal supplement curing a cold but then throw in how getting a good nights sleep every night affects your body’s ability to shake off the cold, then ask the other person what else affects the recovery and how then one tells amongst those other effects whether or not that the supplement actually had an effect.)

First, whether an anecdote is relevant or not depends partly on what it’s used to argue against. The smoking example is a good one. If the general argument is that smoking kills (implying always), a single anecdote to the contrary shows that the argument is false. If the argument is that smoking is a risk factor, then a single anecdote has no particular relevance.

Second, an anecdote doesn’t need to be a scientific study to be relevant. Scientific studies are tools to draw broad conclusions about phenomena. The data set used to draw a conclusion must be controlled. But when that conclusion is applied to the world as a whole, there is no control, it’s assumed that the conclusion is universally valid.

Probably the strongest argument against anecdotes is that they aren’t *documented.* Suppose Buba says his grandad lived to 99 yrs smoking four packs a day. Buba may know it for a fact. But buba didn’t document Grampa Buba’s smoking habits, so everyone else must accept or reject Buba’s “data” on the basis of trust. However, if Buba does know it for a fact, he can indeed reject the theory that “smoking kills.” In other words, buba *can* have information not available to the broader scientific community.

What the scientists are forgetting about is that nature has designed each and every one of us to hold our own trials every nano second of everyday with intrinsic biological systems. Our survival at the end of the day depends on us as individuals and not some clinical trial done in a different geographical and cultural zone to us which may not have a bearing to us. There are so many variables that researches can not possibly control them all. By definition, the evidence based process is like a huge juggernaut that is very late with coming up with solutions that the ordinary public have discovered for themselves long time ago. And people are more than statistics. Statistics depress people. And the minority who suffer as a consequence of statistics are just ignored and told it is all in their minds and that there is no clinical evidence for it. It is high time, the scientist got off their high horses and got real about what is going on with the health of the masses. It is no good sticking their heads in the sand pit in their labs and tell the world to go away until they have finished their meta analysis which is probably meaningless anyway! People are suffering, one in three are having cancer, obesity and related diabetes, heart conditions, etc are epidemic and so are a host of diseases. We are spending billions on health care. People want real answers. Not some drugs with worse side effects than the disease, that have no chance of curing anything. Scientists, stop being so smug and offensive about ordinary people trying to make a difference in their lives and treating us as oxymorons who do not know what a clinical trial is. And get on with it, and really find a cure for our ailments instead of boasting how wonderful you and your methods are! It is getting tiresome…

I think there are two problems that you’re touching on here: one is that people see scientists as stereotypes (egotistical, self-congratulatory, cold-hearted, calculating), and the other is a lack of science literacy among the general public. Now, my fields are climate, ecology, and geography, so I can’t speak as much to medical science (or medical scientists). Certainly some scientists are egotistical jerks– just like some people are egotistical jerks. And certainly there are plenty of issues with, for example, the pharmaceutical industry (remember what I said in my post about who funds the research? That applies in all directions). But by relying on generalizations and caricatures, you’re throwing the baby (science) out with the bathwater (poorly-designed studies, or poor bedside manner).

As for science literacy, you’re contradicting yourself when you say that the evidence-based process is useless, and people are highly diverse, but that you want “real answers” from scientists. Scientists recognize that our models are a simplification of the world, and that the studies we do can never account for every possible variable. Science is a process, just like any creative endeavor, and it takes time (and the process is not linear!). The way I presented science in this post is pretty simplistic – one could write an entire blog about it, let alone a post! For more on this, check out How Science Works, a website created at Berkeley: http://undsci.berkeley.edu/article/0_0_0/howscienceworks_01

Unfortunately, the majority of the public knows very little about how the scientific process works, or what scientists are really like for that matter; that’s something that educators and scientists (and I include myself) need to work pretty darned hard on. There are many fantastic science communicators and scientist bloggers out there that are working very hard on this very thing. I urge you to seek these folks out– some of them are linked on my Blogroll. I know I, for one, am not on a high horse. The more I learn about the natural world, the more I realize I don’t know!

I would like to add that the fact that models are simplifications of reality is not always a bad thing! The results you get from simplified models can give much more insight into the underlying physical processes than the results you’d get from an all-encompassing model — simply because there are too many variables! As a physicist who works with disordered organic semiconductor systems, everything i deal with is a vast oversimplification. As the name implies, the systems I study are disordered; if you wanted to make a perfect realistic model, you’d have to model every atom in the device, because every one is in a different position/state than every other one. The beauty of using a simplified model is that 1) it’s tractable, not only to huge computers, but to people as well. Because we can hold all of the relevant ideas in our heads at once we can 2) develop intuition for how the system’s behavior will change when we make changes to the system. 3) even if our model isn’t exactly reality, we can develop theory around it and know everything there is to know about the model. so even though there aren’t spherical cows, we DO know everything there is to know about spherical cows. …and hopefully real cows are close enough to spherical cows that we can say a lot about those as well.

This may sound strange, but it’s an extreme example of something we deal with every day in the medical world: we’re all humans, but every human is different. If we couldn’t use simplified models, we’d have to re-develop medicine from the ground up for each individual person. If we had to come up with new cures on a case-by-case basis each time someone was sick, we’d never cure anything! Because we can simplify the body and treat everyone as the same, we can actually make progress.

Similarly, even if we treat everyone as the same, the body is enormously complex, so we have to simplify THAT model to be able to do anything useful. This works most of the time, but because we still don’t understand everything about it, unknown effects can surprise us. Hence, we develop drugs that work to address the symptoms we target them to, only to discover that they have side-effects worse than the symptoms. This is unfortunate, but isn’t something that scientists did wrong (more specifically, it’s not because someone screwed up). It’s because we don’t understand 100% of how the body works, but people are dying every day. We can’t wait until we’re 100% sure of how a drug works before it’s released because that would take hundreds of years, and even then we probably wouldn’t know everything about its interaction with the body unless we understood everything about the body. The solution that maximizes the utility we get from drug research is to release it when it’s passed enough trials to convince us that it’s probably safe enough to use and probably is effective on the disease it’s meant to treat. Of course, because we’re only 95% sure, 5% of the time the drug ends up pulled from the market because of unknown side-effects or something else.

If the general population could have come up with a cure for caner, then it would have done so long ago. And if you want a drug that actually works, and has less side effects than the actual disease, then you’ll need to test that drug, many times, to make sure it works, and does just cure you, then kill you anyway. And testing it well means science.

As for curing obesity, diabetes and heart conditions, scientists have told us what we need to do to cure those things: eat better. If you want a pill to cure all those things, then who’re you expecting to come up with that, if not scientists?

Yes, statistics can be depressing. Everyone wants to think they can win the lottery, no matter the chances. But that’s no way to run a country, or cure a disease, or even live your life. Yes, 1 in a 1000 chance means that hundreds of people on the internet will have a story that is that 1 in a 1000, and will be much more likely to share that story. That doesn’t help the 999 in a 1000 at all.

It is evident that you, in no way, understand what research is. I go in and bust my ass every day in hopes of helping people. I fight constantly against what is considered “good enough” by many so that I can try to make cancer treatments more effective and safer. It is because we work as hard as we do and are so concerned with the good of the “ordinary people” (as you call yourself) that cancer is no longer a guaranteed death sentence, many heart problems can be repaired, diabetes can be treated, and surgeries are always getting safer. I take a great deal of offense, as would most of my colleagues, to your hateful attitude towards people who spend their days, nights, weekends, and holidays doing everything they can to get closer to having the “real answers” you claim we are not working toward. There is nothing “smug” or “offensive” about the fact that we give up higher paying career options with better hours to try to help people (some of whom act as though we don’t care about anyone but ourselves).

It was a dig at so called “skeptics” who seem to have given up medicine and science and gone into publishing and journalism to put down alternative therapies. They are actively campaigning for people who have cancer not to have massage therapies because one clinical trial of a handful people have come up with the result that women who have their ovaries removed and having chemotherapy did not show that “quality of life has improved”. And I quote, “The absence of such a result should, in my view, make us think critically about the value of integrative medicine.” According to Cancer Care, people report that massage makes them less lonely and less scared when they go home at the end of a treatment. To campaign to deny people massage because of one trial seems to border on cruel application of scientific principles and dogmas and are out of date in a caring society. This is just one example of many. I came across this blog on one skeptic’s twitter page who regularly rants that all CAM is quackery and public who use them are “evangelical believers in quackery”, and similar insults. It was an unfortunate association and was not meant to be offensive towards hard working scientists such as yourself who are trying to make a difference.

However, there is a grain of truth in what I said. Cancer Care has announced that nearly half of cancers are due to diet and lifestyles and so is diabetes, heart conditions and and a number of other illnesses. Many people are so sold on advertising and “take aways” and “all you can eat” meals that they have forgotten what a good diet is or indeed do not know how to cook anymore. Some have never heard of names of a number of vegetables and fruits let alone eat them. They drink gallons of soft drinks and alcohol instead of water. They get addicted to unhealthy food and drinks. They lose their energy and stop moving. They get in a negative spiral and do not have the know how to pull out of it and need help. Teenagers are getting gastric bands and stomach operations. People have no idea how stress is affecting their health and what to do about it. Two in three of us are either overweight or obese in the Western world and eating garbage and suffering from related diseases. Scientists’ telling us “to eat better” is not working (David) so much so that governments and economists are holding conventions to stem the crisis.

According to one imminent scientist at least, it is in part due to prolonged stress which makes our hormones go haywire and we lose control of our eating and once we have put on the fat, stress is self perpetuating and things like “self control” go out of the window and a lot of diseases ensue. Now, that brings us back to alternative medicine which according to the public at least help with the “relaxation response” to reduce fear and stress.

What is desperately needed is education in preventative medicine for both the public and the scientists and definetely a medical strategy and guidance to halt and reverse the stress/obesity/junk food/addictions epidemic and its related disorders which are on a meteoric rise.

That would theoretically minimise a lot of suffering all around and you may be able to take that well earnt holiday…

Very clear and useful post. I stumbled in here because one of my friends shared it on FB and I liked the title. And now even in the comments I learn new things – I hadn’t even known the word ‘envirofascism’ before :)

I don’t agree with the last take home message: “you don’t have to be a scientist to successfully argue with one!”
If someone follows all your advises he/she will end up thinking like a scientist. But, if you think like a scientist you are a scientist :-)
Anyway, great post. I liked it so much that I added your blog to my bloglist.

>but scientists are liars
The odds that some scientists are liars are what makes the scientific method itself so important – it’s the evidence and the ability for others to replicate findings that means it doesn’t actually matter too much if some do make stuff up, be it to suit an agenda, for personal self-aggrandisement or whatever: not all scientists are liars, and not all have the same agenda.

That’s why when a consensus is reached, by convincing a majority of the validity of whatever result, it is really rather important. It doesn’t guarantee it being right, but you need to come up with something even more convincing to prove it wrong.

I stopped arguing with people about these sorts of things long ago. For an example as to why see Brett’s comment above. There is nothing I can say that’s going to change his mind. And if that’s the case then all the science in the world will not convince him. So . . . I don’t waste my time.
P

This is understandable. However, as long as scientists decide they don’t need to talk to the public (which isn’t what you’re saying here, but it’s related), the more of these folks there’ll be. As a publicly-funded scientist, I do feel as though I have a duty to make myself available, and to engage when I can. Often, I do it not for the benefit of the Bretts in the world, but for those who are silently observing on the sidelines, and haven’t made up their minds yet.

I disagree on “that’s not scientific”. I find that argument is used by *nonscientists* trying to eliminate an argument they don’t like and can’t refute. In practice, the scientific method is extremely pragmatic.

I agree that the scientific method is pragmatic! I personally have never come across a non-scientist saying something ISN’T scientific, but, if they did, they’d probably be using it incorrectly, if they did it as you say. Of course, this is just anecdotal… :)

Let us exchange the word ‘peers’ for ‘colleagues’ so as to gain considerable accuracy and perspective, shall we? The fallacy of the peer-reviewed consensus should be obvious to scientists more than anyone. The very idea that publicly funded scientists are altruistic and interested in nothing but pure research is an embarassment, but when you toss in the idea that they could hardly be less concerned with conclusions (which you did) that transcends nonsense and enters the realm of hubris.

The whole nonsensical article suffers from a lack of logic and an underlying assumption/agenda: anthropogenic global warming. AGW was proposed and is supported by vested interests: the lucrative positions in the UNIPCC alone, not to mention the astronomical increases in departmental budgets, grants and programs that can in any way involve the notion of climate change, would make any person outside this clique skeptical.

It is not surprising to me at all that the Anthropogenic Global Warming lobby spends much more time and effort on propaganda efforts than on research. In fact the bulk of the ‘research’ consists of computer modeling, based on data that is certainly incomplete and probably inaccurate through both omission and manipulation.

I have seen few articles that so well demonstrate the elitist, arrogant hubris of the envirofascism movement. I cannot use the adjective ‘scientific’ or indeed the noun ‘science’ as I do believe in the search for truth that is science – I just do not feel that applying either of these words to the AWG lobby is insulting and misleading.

But the real question is how is Brett so convinced of these things he wrote? He didn’t do all the research that HE’S citing. He read it somewhere. Was that somewhere a place with scientific authority? No, because we know that 99% of scientists agree that he’s wrong. The only explanation is that he liked what he read better than the truth and chooses to wear blinders. If Brett were objective, he wouldn’t be so sure that 99% of the very smart people doing that climate research were wrong.

Yeah I know how you feel, Brett. All my friends who work in climate science are just ROLLING AROUND on $100 bills, eating fine caviar and drinking Dom Perignon during their 3-hour lunch at the country club.

BTW – way to take the article about arguing with scientists and using NOTHING provided within said article in your post.

I partially agree with Brett. To think that the opinion leaders in the field do not try to mitigate uncomfortable views is indeed a little naive. Have you never witnessed a debate where two scientists go at each others throat for coming to different conclusions based on identical facts?
Regarding global warming, CO2 levels and temperatures are correlated. That doesn’t necessarily mean that they are causally related or allows to say for sure to what degree one is causing the other. Especially when it comes to climate forecasts based on computer models a bit more caution by the news media would be desirable.

Brett has provided an excellent example of exactly the types of failed arguments I was referring to! His comment also includes a number of other common characteristics of bad arguments that aren’t limited to debating with scientists, including ad hominem attacks, derailing, straw man arguments, and logical fallacies. I don’t have time to go into these in detail, but I urge readers to look them up if you’re interested in making better arguments in general.

In this case, the scientist will probably not respond to Brett, for several reasons. First, he grossly misrepresented the scientists’s words and ideas (examples: “lobby,” “altruism,” “arrogant hubris”). Notice that Brett has basically created a caricature of what the scientist actually said– his comment is so far off-base that it’s honestly difficult to respond to– and the ways in which Brett has twisted the scientist’s words reflect more about Brett and his biases than the scientist’s ideas themselves. (Pro-tip: limit your arguments to what is actually being said in any particular argument with a particular scientist, not with an imaginary version of that conversation. Do not assume that any one scientist speaks for all of Science, for all time. This is a very ineffective way to argue!).

Brett’s tactics may infuriate the scientist (this is what is known as “trolling” in the world of the Internet). This may be his (or your) goal, but it’s not the same thing as making a successful argument (the topic of this guide). Brett’s tactic may be to mislead or misdirect the scientist into talking about something other than the relevant science; in fact, the scientist may spend a great deal of time trying to reign in the discussion and correct the numerous flaws in arguments like the one Brett has made. If his (your) goal is to waste a scientist’s time, he may have succeed, but it’s also not the same thing as winning an argument. The scientist may ultimately throw up their hands in utter frustration, ignore Brett (you), laugh, and even delete his (your) comments (especially if it’s particularly hateful, inappropriate, or off-topic): this is also not the same thing as winning an argument.

Remember: The goal is to successfully argue with scientists! Anything else is just a waste of time, and will probably even make you look bad.

The first scientist who manages to show, in a rigorous, replicable, elegant experiment, that Climate Change is either not happening, or not human caused, will be incredibly famous and rich. Probably get a Nobel prize.

Stop. Think about that.

No, really, think about it.

Also, you were so busy frothing at the mouth you managed to contradict yourself in your final statement – Freudian?

Seriously, if you cant control your own words, maybe you should examine the possibility that you are a wingnut. It may be that you are just an idiot, and should stop commenting on things that are out of your grasp. This is not rare. There are a lot of people out there who just dont have the capacity to understand complex matters.

i am certainly not cringing, this is a great primer. It helps those of us that have tried to explain this information to friends that think scientific debate equals an attack on them. A significant part of public science literacy is what has been explained so well here in your post. It is disappointing when a scientist attempts to participate and is shunned due to misunderstanding. i have seen that happen and linking to this information will prevent further missed opportunities for improving public engagement with science.